The past decade has seen the introduction of high throughput experimental and computational methods that promise to revolutionize the approach to, and understanding of, the biology of the cell. We propose to build on this foundation by developing the computational tools and methods that will enable researchers to begin to understand collective cellular properties, and by substantially strengthening an educational program designed to train a new generation of biologists who can use these methods creatively. The goal is to develop and make widely available a large array of techniques that build upon concepts from statistics, computer science and theoretical chemistry, and to develop a system that takes advantage of their synergistic nature, and that allows integration of new and existing data upon which the methods would operate. As a demonstration project we focus on two well studied pathways related to the regulation of growth and apoptosis in a human cell line, and test the ability of these methods to unravel the relation between these pathways and the cascades of genes and proteins that they modulate. Plans for an organization that will educate the next generation of biomedical researchers, while creating new methodologies and advancing biomedical science will be developed by a large group of faculty from computer science, the experimental and clinical sciences, and statistics.